Modeling and air quality assessment through Grey Clustering analysis, case study: Lima Metropolitana

Abstract

Currently, the criteria to air quality assessment are analyzed independently, leaving aside the systemic approach of the environment, where air quality is influenced and controlled by many types of factors, where several parameters interact and mutually restrict each other for that reason a higher evaluation system is proposed by Grey Clustering analysis based on fuzzy logic, which takes into account the high degree of uncertainty present in the environment. The methodological proposal will assess the quality of air in Lima Metropolitana. In this work, we apply Center-point triangular whitenization weight functions (CTWF) method, where it will be demonstrated that the proposed model is exact, comparable and applicable. The monitoring data on each city of Lima Metropolitana were obtained from National Service of Meteorology and Hydrology of Peru – Senamhi. The CTWF method was applied using parameters of air quality such as PM10, PM2.5, SO2 y N02. Then, the results were ranked using the Year Average Common Air Quality Index (YACAQI). Consequently, the results showed that most of the cities are polluted. Finally, the results of this study could be used by local authorities or central government to make the best decision to focus on the main persistent pollutants in the environment.